The fundamental function of ribonucleic acids is to transfer genetic information from DNA to protein during translation process, however, this is not the only way connecting active RNA sequences with essential biological processes. Up until now, many RNA subclasses of different size, structure, and biological function were identified. Among them, there are non-coding single-stranded microRNAs (miRNAs). This subclass comprises RNAs of 19–25 nucleotides in length that modulate the activity of well-defined coding RNAs and play a crucial role in many physiological and pathological processes. miRNA genes are located both in exons, introns, and also within non-translated regions. Several miRNAs that are transcribed from the adjacent miRNA genes are called cluster. One of the largest ones is miR-17-92 cluster known as OncomiR-1 due to its strong link to oncogenesis. Six miRNAs from the OncomiR-1 have been shown to play important roles in various physiological cellular processes but also through inhibition of cell death in many cancer-relevant processes. Due to the origin and similarity of the sequence, miR-17-92 cluster and paralogs, miR-106b-25 and miR-106a-363 clusters were defined. Here we discuss the oncogenic function of those miRNA subgroups found in many types of cancers, including brain tumors.

Encephalocraniocutaneous lipomatosis (ECCL) is a rare neurocutaneous disorder, with only about 100 cases reported worldwide. It is characterized by congenital lesions of the eye, skin, and central nervous system. Only recently, potential causative FGFR1 point mutations have been identified in brain tumors and cultured skin biopsies from patients with this condition. Here, we analyzed the molecular status of a patient with ECCL and a coexisting pilocytic astrocytoma with detected FGFR1 N546K mutation.The presence of the alteration in both affected and unaffected tissues has been evaluated using Sanger sequencing and droplet digital polymerase chain reaction (ddPCR) technique. The ddPCR analysis showed differential distribution of the alteration in all specimens, including unaffected and untreated samples. Therefore, we confirm that FGFR1 N546K is a plausible causative mutation of ECCL patients and could be associated with a risk of brain tumor development. We also show the usefulness of sensitive ddPCR method for detection of low levels of autosomal mosaic mutation in blood or swabs. We suggest that utilization of this method may improve the diagnostic process, especially when targeted therapies are considered.

Numerous molecular factors disrupt the correctness of the cell cycle process leading to the development of cancer due to increased cell proliferation. Among known causative factors of such process is abnormal gene expression. Nowadays in the light of current knowledge such alterations are frequently considered in the context of mRNA–miRNA correlation. One of the molecular factors with potential value in tumorigenesis is the feedback loop between MYC and E2F genes in which miR-17-5p and miR-20a from the miR-17-92 cluster are involved. The current literature shows that overexpression of the members of the OncomiR-1 are involved in the development of many solid tumors. In the present work, we investigated the expression of components of the MYC/E2F/miR-17-92 network and their closely related elements including members of MYC and E2F families and miRNAs from two paralogs of miR-17-92: miR-106b-25 and miR-106a-363, in the most common brain tumors of childhood, pilocytic astrocytoma (PA), WHO grade 1; ependymoma (EP), WHO grade 2; and medulloblastoma (MB), WHO grade 4. We showed that the highest gene expression was observed in the MYC family for MYCN and in the E2F family for E2F2. Positive correlation was observed between the gene expression and tumor grade and type, with the highest expression being noted for medulloblastomas, followed by ependymomas, and the lowest for pilocytic astrocytomas. Most members of miR-17-92, miR-106a-363 and miR-106b-25 clusters were upregulated and the highest expression was noted for miR-18a and miR-18b. The rest of the miRNAs, including miR-19a, miR-92a, miR-106a, miR-93, or miR-25 also showed high values. miR-17-5p, miR-20a obtained a high level of expression in medulloblastomas and ependymomas, while close to the control in the pilocytic astrocytoma samples. miRNA expression also depended on tumor grade and histology.

Background The understanding of the molecular biology of pediatric neuronal and mixed neuronal-glial brain tumors is still insufficient due to low frequency and heterogeneity of those lesions which comprise several subtypes presenting neuronal and/or neuronal-glial differentiation. Important is that the most frequent ganglioglioma (GG) and dysembryoplastic neuroepithelial tumor (DNET) showed limited number of detectable molecular alterations. In such cases analyses of additional genomic mechanisms seem to be the most promising. The aim of the study was to evaluate microRNA (miRNA) profiles in GGs, DNETs and pilocytic asytrocytomas (PA) and test the hypothesis of plausible miRNA connection with histopathological subtypes of particular pediatric glial and mixed glioneronal tumors. Methods The study was designed as the two-stage analysis. Microarray testing was performed with the use of the miRCURY LNA microRNA Array technology in 51 cases. Validation set comprised 107 samples used during confirmation of the profiling results by qPCR bioinformatic analysis. Results Microarray data was compared between the groups using an analysis of variance with the Benjamini-Hochberg procedure used to estimate false discovery rates. After filtration 782 miRNAs were eligible for further analysis. Based on the results of 10 × 10-fold cross-validation J48 algorithm was identified as the most resilient to overfitting. Pairwise comparison showed the DNETs to be the most divergent with the largest number of miRNAs differing from either of the two comparative groups. Validation of array analysis was performed for miRNAs used in the classification model: miR-155-5p, miR-4754, miR-4530, miR-628-3p, let-7b-3p, miR-4758-3p, miRPlus-A1086 and miR-891a-5p. Model developed on their expression measured by qPCR showed weighted AUC of 0.97 (95% CI for all classes ranging from 0.91 to 1.00). A computational analysis was used to identify mRNA targets for final set of selected miRNAs using miRWalk database. Among genomic targets of selected molecules ZBTB20 , LCOR , PFKFB2 , SYNJ2BP and TPD52 genes were noted. Conclusions Our data showed the existence of miRNAs which expression is specific for different histological types of tumors. miRNA expression analysis may be useful in in-depth molecular diagnostic process of the tumors and could elucidate their origins and molecular background. Electronic supplementary material The online version of this article (10.1186/s12885-019-5739-5) contains supplementary material, which is available to authorized users.